Staff Machine Learning Engineer, Support

Lead the end-to-end delivery of multiple machine learning initiatives from planning and design through rollout, documentation, and long-term maintenance. Partner with risk, product, engineering, design, and operations leaders to define and execute long-term ML roadmaps. Guide team direction, identify ML and AI opportunities, and advise leadership on strategic tradeoffs. Drive R&D on chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference. Design, deploy, and maintain ML models for conversational agents and support chatbots across Block products. Develop ML-powered agent tools and real-time recommendation systems to improve support effectiveness and customer outcomes. Represent the team’s systems and programs to stakeholders, cross-functional partners, and external audiences. Responsibilities Lead the end-to-end delivery of multiple machine learning initiatives from planning and design through rollout, documentation, and long-term maintenance. Partner with risk, product, engineering, design, and operations leaders to define and execute long-term ML roadmaps. Guide team direction, identify ML and AI opportunities, and advise leadership on strategic tradeoffs. Drive R&D on chatbot architectures using LLMs, RAG, fine-tuning, and real-time inference. Design, deploy, and maintain ML models for conversational agents and support chatbots across Block products. Develop ML-powered agent tools and real-time recommendation systems to improve support effectiveness and customer outcomes. Represent the team’s systems and programs to stakeholders, cross-functional partners, and external audiences. Requirements 10+ years of experience in machine learning, applied AI, or product ML, with deep technical expertise. Demonstrated ability to influence and align cross-functional teams while shaping peers’ work through technical guidance and communication. Track record of organizational-wide impact through systems, frameworks, or initiatives spanning multiple teams or functions. Proven ability to ship end-to-end ML features from problem framing through deployment and long-term maintenance. Production experience with language models, dialog systems, or generative AI. Strong foundation in NLP, deep learning, or ML infrastructure best practices. Excellent communication skills for representing technical work to leadership and stakeholders. Enthusiasm for R&D and advancing applied AI for conversational systems. Benefits Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning benefits are offered. Compensation varies by location and is organized into four U.S. labor-market zones. The company provides an inclusive interview experience and reasonable accommodations for disabled applicants. #J-18808-Ljbffr Block USA